Aiming at the problem that the existing adaptive prediction methods of remaining useful lifetime (RUL) for the airborne electronic equipment fail to comprehensively consider the hidden degradation modeling and online drift coefficients updating in the condition of newly researched and small sample

an adaptive prediction method for the airborne electronic equipment’s RUL based on the EM-EKF algorithm and hidden degradation model with proportion relationship is proposed. Firstly

based on the nonlinear Wiener process

a hidden degradation model with the proportion relationship is constructed. Next

the degradation state equation of the equipment is established based on the drift coefficient update mechanism

and the EKF algorithm is used to update the degradation status and drift coefficient. And then

the EM-EKF algorithm is used to adaptively estimate the parameters of the degradation model. Finally

based on the full probability formula

the probability density function (PDF) of RUL is derived. By analyzing the measured data of a single micromechanical gyroscope

it is verified that the proposed method has better model fitting and prediction accuracy.